In recent years, a user application, especially, a mobile application, installed and operated in a mobile terminal, develops rapidly. In order to make it convenient for a user to select and install an application, many application websites or application stores provide services on an application collectively, such as, a search service, a download service and a rating service, and also publish an application leaderboard regularly, for example, every day, to present some applications popular with users currently. In fact, the leaderboard is a valued means to prompt applications. An application with a high ranking in the leaderboard generally stimulates a large number of users to download the application, which brings a large economic income for an application developer.
And, from the technical perspective, a ranking of an application in the leaderboard represents the popularity of the application with users, and therefore, it is possible to learn about technical information, commercial information and the like, which are hidden behind these applications popular with users, by analyzing data related to the leaderboard, such as a development trend of a related technical field, an operation mode of a commercial advertisement, and even a ranking fraud to obtain a false high ranking in the leaderboard in a fraudulent manner. However, the prior art lacks studies on information about an application leaderboard, and moreover, lacks technologies for analyzing and processing information about an application leaderboard.